Multi-objective Particle Swarm Optimization Biclustering of Microarray Data

With the advent of the DNA microarray technology,it is now possible to study the transcriptional response of a complete genome to different experimental conditions. Biclustering is a very useful data mining technique for analysis of those gene expression data.During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective modeling is suitable for solving biclustering problem. This paper proposes a novel multi-objective particle swarm optimization biclustering (MOPSOB) algorithm to mine coherent patterns from microarray data. Experimental results on real datasets show that our approach can effectively find significant biclusters of high quality.